-By Ravi Kiran, CTO, Payswiff Solutions
Today, artificial intelligence has touched every aspect of our lives. From asking our smartphones for nearby restaurants, commanding smart devices to play music, book cabs and reorder groceries to even having a conversation with our refrigerators. Thanks to deep learning and interoperability, these appliances have inbuilt ability to learn our habits over time and communicate with us. To simply quote Google CEO Sundar Pichai “Artificial intelligence is going to have a bigger impact on the world than some of the most ubiquitous innovations in history. AI is one of the most important things humanity is working on. It is more profound than, I don’t know, electricity or fire”
A recent global study from Pega found that 72 per cent of people now understand what AI is and that only 28 per cent people are uncomfortable with the thought of it.
Increased Operational Efficiency
When it comes to AI, some of the primary considerations of Banks and Financial Institutions is to explore how AI can help them refine their front end and back end activities. It is helping payment companies in improving their operational workflows which can reduce human error and result in reduced processing times. AI has significantly made gains in enhancing processes, automate mundane manual tasks that typically involve large number of resources.
More Informed Decisions
AI is helping businesses to restructure operating models and processes based on processing huge amount of data by creating various financial and other reports for business decision making. It is playing a vital role in analyzing enormous amounts of customer data and present key insights and recommendations based on their patterns.
According to Gartner, by 2020 chatbots will be handling no less than 85% of all customer service interactions
AI Powered Chatbots
With customers relying heavily on their smartphone for banking and payment activities; financial institutions are leveraging on chatbots solutions that are designed to enhance experience engage via text and voice. This eliminates the need of managing resource-based support to quick service, transactional support and address basic needs of customers. Erica from Bank of America, Eno from Capital One, Khushi from PnB MetLife are just few examples of how financial institutions are using chatbots to provide support 24/7.
Detecting Fraud & Minimizing Risks
By 2020, global merchants are expected to be processing 726 billion digital payments every year and with such huge volumes, fraudulent activities cannot be eliminated 100%. Artificial Intelligence can help us in predicting frauds by analyzing the historical risk data, reducing false positives and raising red flags for any future payments. For card not present scenario, it can help uncover patterns and drive hidden insights. Instead of relying on supervised learning with input, advances are allowing companies to move past this more static model to unsupervised learning. It will continuously update the model as new pattern emerges, allowing for a more robust, flexible, and updated fraud prevention detection tool.
Challenges Ahead
With Real-Time-Payments (RTP) now a reality – payment holds, delays and any reservations are removed; giving merchants instant access to their completed sales amount in seconds. But, this also brings in the challenge of finding fraud & taking action within seconds, which needs to be addressed. Though in consumer vertical, artificial intelligence has gained immense popularity, it is in the payments domain that it is being limited due to lack of proof points. With further developments in machine learning, we’re hoping for a full utilization of this technology.
Still a Long Way to Go
Industry leaders have begun reaping the benefits of implementing AI in their processes and systems. As it uncovers new insights and brings further advancements in the coming years, the full potential of AI is yet to be uncovered. We have just scratched the surface and a lot of work needs to be done as the opportunities presented are huge, especially in the payments landscape.